Youtuber Ominous Industries provides a training video for setting up your Jetson Nano, installing Pytorch and setting up your own (likely open source LLM).


This takes the NVIDIA Jetson Nano to the next level by training a Large Language Model (LLM) completely from scratch. It uses the lightweight and efficient NanoGPT framework,
This covers setting up your environment to running your very own trained model.
This work is taking what Andre Karpathy did for teaching people how to make an LLM and applying to the Nvidia Nano developer kits.
He begins by preparing the Jetson Nano with all the necessary tools, including installing and testing PyTorch.
The concept and processes of tokenization, dataset preparation, and optimizing the Jetson Nano for training efficiency are reviewed.

He shows the training process and demonstrate how to run the trained model directly on the device.

This guide is perfect for beginners and AI enthusiasts looking to explore LLM training on affordable hardware. With a focus on step-by-step instructions, you’ll be able to replicate the process and unlock the power of local LLMs on your Jetson Nano.
Timestamps:
00:00 – Intro
01:08 – Setting Up Our Environment
05:30 – Installing Pytorch
13:50 – Testing Pytorch
09:00 – NanoGPT Setup
16:03 – Understanding Tokenization
23:24 – Data Set Prep
24:20 – Training Intro
27:33 – Training Setup
33:48 – Jetson Optimizations
36:10 – Training The Model
40:05 – Running The Model
45:38 – Closing Thoughts
https://gist.github.com/OminousIndustries/109672cc8f32bf1ea1998bd986f6b96a
Amazon – Jetson Nano 4GB RAM 16G eMMC for $215 (and a 5% coupon to get to about $204).
Amazon Nvidia Jetson Nano 2GB Developer without Wifi $160.

Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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